Student achievement in secondary education of two Portuguese schools.
This repository contains the related materials for the Student Performance Analysis in Portuguese Secondary Education. The project aims to utilize machine learning techniques to analyze factors influencing student achievement and develop predictive models.
The project is organized with the following files:
- .gitignore: Specifies patterns to be ignored by version control, ensuring certain files are not tracked by Git.
- README.md: Provides essential information about the project, its purpose, and the structure of the repository.
- Datasets/: Directory containing links to the datasets used in the project.
- visualization.ipynb: This Jupyter Notebook is dedicated to data visualization techniques, allowing for a clearer understanding of trends and patterns in the dataset.
The dataset utilized in this project is sourced from Portuguese secondary schools and comprises comprehensive information on student achievement. It encompasses a wide array of attributes, ranging from demographic and social factors to school-related metrics, providing a holistic view of the factors influencing student performance.
- Dataset: Kaggle, UCI Machine Learning Repository
- Documentation: DSI UMinho